Protein markers for detecting liver cancer and method for identifying the markers thereof

ABSTRACT

The present invention relates to the diagnosis of liver cancer. It discloses the use of protein ERBB3 and protein IGFBP2 in the diagnosis of liver cancer. It relates to a method for diagnosis of liver cancer from a liquid sample, derived from an individual by measuring ERBB3 protein and IGFBP2 protein in the sample. Measurement of ERBB3 protein and IGFBP2 protein can, e.g., be used in the early detection or diagnosis of liver cancer.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a division of U.S. patent application Ser. No. 12/831,447, filed on Jul. 7, 2010, titled Protein Markers for Detecting Liver Cancer and Method for Identifying the Markers Thereof, listing Sen-Yung Hsieh as inventor.

FIELD OF THE INVENTION

The present invention relates to protein markers for detecting liver cancer, also called hepatoma, in plasma or serum and a method for detecting liver cancer thereof. The present invention also relates to a method for identifying a novel marker in plasma/serum for detecting liver cancer. In particular, the present invention relates to protein markers expressed in tissue interstitial fluid and a method for identifying novel marker in a tissue interstitial fluid for detecting liver cancer. Especially, the present invention relates to plasma/serums ERBB3 and IGFBP2 protein markers used for detecting liver cancer precisely.

BACKGROUND OF THE INVENTION

Cancer remains a major public health challenge despite progress in detection and therapy. Whole blood, serum, plasma, or nipple aspirate fluid are the most widely used sources of sample in clinical routine. Conventionally, researchers try to find valuable markers from plasma/serum to detect liver cancer. However, up to 90 percentage of the plasma/serum are composed by 6 constant serum proteins, and 99 percentage are composed by about 20 constant proteins. The metabolic and the physiological conditions could be represented in whole blood, serum or plasma. Some specific proteins with diagnosis values are secreted into whole blood, serum or plasma, but they always present in a trace amount and are hard to be found. Therefore, an urgent clinical need exists to improve the method to identify biomarkers for the diagnosis of liver cancer from plasma/serum.

Some researchers tried to find tumor markers from hepatocellular carcinoma (hereinafter may be referred to as “liver cancer”, “hepatoma” or “HCC”) tissue or cell culture media. However, neither tumor tissues nor cell culture media of hepatocellular carcinoma has been proved to be an adequate source for identifying new serum markers for hepatoma. In contrast, the tissue interstitial fluid is the media between tumor cells and the circulation, and tumor interstitial fluid represents the microenvironment that tumor cells inhabit. Tumor markers shed into circulation may also be generated by interaction of tumor cells with its microenvironment. It is, therefore, tempting to examine whether tumor interstitial fluid is the source for discovery of serum biomarkers.

So far, some markers, including alpha-fetoprotein (AFP), alpha-fetoprotein lectin fraction-L3 fraction, PIVKA-II, AFU and GPC3, have conventionally been employed for liver cancer diagnosis. However, results obtained from detecting by the foregoing tumor markers often show false-positive or false-negative, so that their functions of detection are limited clinically. Despite the large and ever growing list of candidate protein markers in the field of liver cancer, to date clinical/diagnostic utility of these molecules is not known. In order to be of clinical utility, a new diagnostic marker as a single marker should be at least as good as the best single marker known in the art. Or, a new marker should lead to a progress in diagnostic sensitivity and/or specificity either if used alone or in combination with one or more other markers, respectively.

Therefore, there is a keen need in the art to develop a new tumor marker for clinical diagnosis and increase the precision of diagnosis. It was the task of the present invention to investigate whether a new marker can be identified which may aid in liver cancer diagnosis. Surprisingly, it has been found that use of the marker ERBB3 or IGFBP2 can at least partially overcome the problems known from the state of the art.

SUMMARY OF THE INVENTION

The present invention therefore relates to a novel protein marker ERBB3 for detecting liver cancer.

The present invention therefore relates to a novel protein marker IGFBP2 for detecting liver cancer.

The present invention therefore relates to a method for the detection of liver cancer comprising the steps of a) providing a liquid sample obtained from an individual, b) contacting said sample with a specific binding agent for ERBB3 or IGFBP2 under conditions appropriate for formation of a complex between said binding agent and ERBB3 or IGFBP2, and c) correlating the amount of complex formed in (b) to the detection of liver cancer.

The present invention also relates to a method for identifying a marker for detecting liver tumor in plasma/serum, comprising:

obtaining fresh tissues of liver cancer and non-cancer liver tissues from patients with liver cancer, cutting the tissues and washing by PBS solution twice, culturing the cut tissues in an incubator for 10 minutes, and then precipitating by centrifugation at 1000-2000 rpm/min for 2-5 minutes to obtain cell pellets and removing the contaminations;

re-suspending the cell pellets in PBS solution, culturing the suspended cells in PBS solution in the incubator for 60 minutes, precipitating by centrifugation at 1000-2000 rpm/min for 2-5 minutes to remove cell pellets and obtain a crude tissue interstitial fluid;

centrifugating the crude tissue interstitial fluids by centrifugation at 5000-15000 rpm/min for 15-30 minutes to remove undissolved cell matrix and obtain a pure tissue interstitial fluid;

comparing the difference of the protein components between the tissue interstitial fluids obtained from the liver cancer tissues and non-cancer liver tissues by proteomic methods, then identifying the relatively high-content proteins in tissue fluids of the liver cancer cells, and listing those relatively high-content proteins as candidate biomarkers for hepatoma detection;

detecting the candidate biomarkers in serum by ELISA and measuring the concentrations of the candidate markers, and

analyzing the concentrations difference by student t-test analysis and Receiver Operating Characteristic curve (ROC curve) to check the function of the candidate biomarkers.

The candidate biomarkers were further used to detect serum samples obtained from liver cancer patients and non-liver cancer patients by ELISA and ROC curve. When area under curve values (AUC values) of the candidate markers in serums are greater than 90%, the protein is classified as suitable markers for hepatoma detection.

Comparing with the conventional method of detecting liver cancer, it is hard to find a suitable marker from serum for detecting liver cancer by the conventional methods. The present invention provides a novel ERBB3 protein and a novel IGFBP2 protein as markers for liver cancer detection. ERBB3 protein and IGFBP2 protein are found from tissue interstitial fluids and have been proven their powerful functions in identifying liver cancers. Detection by the concentrations of ERBB3 protein and IGFBP2 protein in patients' serum/plasma or whole blood could increase the sensitivity of liver cancer diagnosis.

As a skilled artisan will appreciate, any such diagnosis is made in vitro. The patient sample is discarded afterwards. The patient sample is merely used for the in vitro diagnostic method of the invention and the material of the patient sample is not transferred back into the patient's body. Typically, the sample is a liquid sample.

A specific binding agent preferably is an antibody reactive with ERBB3 or IGFBP2. The term antibody refers to a polyclonal antibody, a monoclonal antibody, fragments of such antibodies, as well as to genetic constructs comprising the binding domain of an antibody. Any antibody fragment retaining the above criteria of a specific binding agent can also be used.

In a preferred embodiment the method according to the present invention is practiced with serum as liquid sample material.

In a further preferred embodiment the method according to the present invention is practiced with plasma as liquid sample material.

In a further preferred embodiment the method according to the present invention is practiced with whole blood as liquid sample material.

In a further preferred embodiment the method according to the present invention is practiced with tissue interstitial fluid of liver as liquid sample material.

Whereas application of routine proteomics methods to tissue interstitial fluid obtained from tissue samples, leads to the identification of many potential marker candidates for the tissue selected, the inventors of the present invention have been able to surprisingly detect both or one of ERBB3 and IGFBP2 in a bodily fluid sample. Even more surprising they have been able to demonstrate that the presence of ERBB3 and IGFBP2 in such liquid sample obtained from an individual can be correlated to the diagnosis of liver cancer.

Antibodies to ERBB3 and IGFBP2 with great advantages can be used in established procedures, e.g., to detect liver cancer cells in situ, in biopsies, or in immunohistological procedures.

Preferably, an antibody to ERBB3 is used in a qualitative (ERBB3 present or absent) or quantitative (ERBB3 amount is determined) immunoassay.

Preferably, an antibody to IGFBP2 is used in a qualitative (IGFBP2 present or absent) or quantitative (IGFBP2 amount is determined) immunoassay.

Measuring the level of protein ERBB3 or IGFBP2 has proven very advantageous in the field of liver cancer. Therefore, in a further preferred embodiment, the present invention relates to use of protein ERBB3 or/and IGFBP2 as a marker molecule in the diagnosis of liver cancer from a liquid sample obtained from an individual.

The details of one or more embodiments of the technology are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the technology will be apparent from the description and drawings, and from the claims. All cited patents, and patent applications and references (including references to public sequence database entries) are incorporated by reference in their entireties for all purposes.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a scheme showing steps performing in accordance with the present invention.

FIG. 2A is a picture showing a two-dimensional gel electrophoresis (2-DE) of Example 1 in accordance with the present invention.

FIG. 2B is a picture showing a two-dimensional differential fluorescence gel electrophoresis (2-D DICE) condition of Example 1 in accordance with the present invention.

FIG. 3 is a picture showing results of normal tissue interstitial fluid and tumor tissue interstitial fluid on a biochip.

FIG. 4 is a chart showing different concentrations of ERBB3 proteins obtained from different tissues.

FIG. 5A is a chart showing ROC curve of serum ERBB3 discriminating hepatoma from non-hepatoma controls in the discovery group in accordance with the present invention.

FIG. 5B is a chart showing ROC curve of serum ERBB3 discriminating hepatoma from non-hepatoma controls in the validation group in accordance with the present invention.

FIG. 5C is a chart showing ROC curve of serum ERBB3 discriminating hepatoma from non-hepatoma controls in the discovery and validation groups in accordance with the present invention.

FIG. 6 is a chart showing different IGFBP2 concentrations in Example 1 obtained from different tissues.

FIG. 7A is a chart showing ROC curve of serum IGFBP2 discriminating hepatoma from non-hepatoma controls in the discovery group in accordance with the present invention.

FIG. 7B is a chart showing ROC curve of serum IGFBP2 discriminating hepatoma from non-hepatoma controls in the validation group in accordance with the present invention.

FIG. 7C is a chart showing ROC curve of serum IGFBP2 discriminating hepatoma from non-hepatoma controls in the discovery and validation groups in accordance with the present invention.

FIG. 8A is a chart showing ROC curve of serum ERBB3, AFP, or combined ERBB3 and AFP in discriminating hepatoma from non-hepatoma controls in one of the present embodiment in accordance with the present invention.

FIG. 8B is a chart showing ROC curve of serum IGFBP2, AFP, or combined IGFBP2 and AFP in discriminating hepatoma from non-hepatoma controls in one of the present embodiment in accordance with the present invention.

FIG. 8C is a chart showing ROC curve of serum IGFBP2, ERBB3, or combined IGFBP2 and ERBB3 in discriminating hepatoma from non-hepatoma controls in one of the present embodiment in accordance with the present invention.

FIG. 8D is a chart showing ROC curve of serum ERBB3, IGFBP2, AFP, or combined ERBB3, IGFBP2, and AFP in discriminating hepatoma from non-hepatoma controls in one of the present embodiment in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The following examples illustrate the invention without limiting its scope.

The present invention relates to a method for the detection of liver cancer, comprising the steps of:

a) providing a liquid sample obtained from an individual,

b) contacting said sample with an antibody specific for at least one of ERBB3 protein (SEQ ID NO:2) and IGFBP2 protein (SEQ ID NO: 4) under conditions appropriate for formation of a complex between said antibody and at least one of said proteins, and

c) correlating an amount of the complex formed in (b) to the detection of liver cancer.

With reference to FIG. 1, the method for obtaining the novel ERBB3 and IGFBP2 protein markers for hepatoma detection comprises the steps of:

Step 1 (11) Obtaining liver cancer tissues and non-cancer liver tissues from individuals respectively:

cutting the obtained liver cancer tissues and the non-cancer liver tissues into 1×1×3 mm³ pellets,

washing the above pellets by PBS solution twice,

incubating the cell pellets by PBS solution at 37° C., 10% CO₂ incubator for 10 minutes,

centrifuging the cultured cell pellets at 1000 to 2000 rpm/min for 2 to 5 minutes to remove the contaminations on liver cancer tissues and non-cancer liver tissues,

Step 2 (12) Separating tissues and tissue interstitial fluid by low speed centrifugation:

culturing the cell pellets by PBS at 37° C., 10% CO₂ incubator for 60 minutes,

centrifuging the cultured broth at 1000-2000 rpm/min for 2-5 minutes to separate tissues and tissue interstitial fluid, and avoiding cell crack,

Step 3 (13) Removing the dissolved matrix by high speed centrifugation,

centrifuging the cultured broth by 5000-15000 rpm/min for 15-30 minutes to increase the purification and the sensitivity of the tissue interstitial fluid,

Step 4 (14) Finding candidate biomarkers for hepatoma detection:

comparing protein pattern obtained from liver cancer tissues and non-cancer liver tissues to select possible protein markers, said protein patterns may be performed such as 2-DE or antibody arrays,

identifying and listing the candidate biomarkers which are present in relatively high concentration and are highly different in the protein pattern of the liver cancer and non-cancer liver tissues.

Step 5 (15) Selecting candidate biomarkers for hepatoma detection proteins:

analyzing the candidate biomarkers by ELISA method and checking the concentrations of each candidate biomarker in cancer tissues and non-cancer tissues,

analyzing the concentrations obtained from the above sub-step by student t-test to identify the concentration of the biomarker with significant difference, and selecting the concentration of the biomarker with p value<0.01,

further analyzing the concentration with significant difference by ROC curve method and selecting the candidate biomarker with AUC value>90% as the biomarker for hepatoma detection.

In a preferred embodiment, the above selected markers were further analyzed by applying in the serum samples obtained from another liver cancer group and non-liver cancer group. The method may be performed by ELISA method and ROC curve method for getting their AUC values. When the AUC values>90%, the selected marker was confirmed to be a suitable marker for liver cancer detection.

As used herein, the term “non-liver cancer” refers to a patient that may have cirrhosis without liver cancer, chronic hepatitis or healthy individuals without liver cancer.

As used herein, “antibody” or “specific binding agent” includes immunoglobulin molecules and immunologically active determinants of immunoglobulin molecules, i.e., molecules that contain an antigen binding site which specifically binds (immunoreacts with) an antigen. Structurally, the simplest naturally occurring antibody (e.g., IgG) comprises four polypeptide chains, two copies of a heavy (H) chain and two of a light (L) chain, all covalently linked by disulfide bonds. Specificity of binding in the large and diverse set of antibodies is found in the variable (V) determinant of the H and L chains; regions of the molecules that are primarily structural are constant (C) in this set. Antibody includes polyclonal antibodies, monoclonal antibodies, whole immunoglobulins, and antigen binding fragments of the immunoglobulins.

In the diagnostic and prognostic assays of the invention, the antibody can be a polyclonal antibody or a monoclonal antibody and in a preferred embodiment is a labeled antibody.

In this exemplary method a Receiver Operating Characteristic curve (ROC curve) is generated. An ROC curve is a plot of test sensitivity (plotted on the y axis) versus its False Positive Rate (or 1—specificity) (plotted on the x axis). Each point on the graph is generated by using a different cut point. The set of data points generated from the different cut points is the empirical ROC curve. Lines are used to connect the points from all the possible cut points. The resulting curve illustrates how sensitivity and the FPR vary together. ROC is a standard statistical method used in the evaluation of a biomarker in disease diagnosis. This analysis determines the ability of a test to discriminate diseased cases from normal cases. The value of the area under the ROC curve is a measure of test accuracy.

EXAMPLE 1 Markers Selection

1-1 Sample Collection and Preparation

Step 1: Liver cancer tissues and non-cancer liver tissues were respectively collected from 10 patients with hepatoma received surgical resection of liver tumors. The contaminations on the liver cancer tissues and non-cancer liver tissues were removed by low speed centrifugation.

In a preferred embodiment of the present invention, liver cancer tissues and non-cancer liver tissues were obtained by surgical operation. The sizes of the tissues were cut as 1×1×3 mm, and then the cut tissues were cultured by PBS solution in an incubator at 37° C. and 10% CO₂ condition for 10 minutes. Then the culture broth was centrifuged at 1000-2000 rpm/min for 2-5 minutes for removing the contaminations on the tissues.

Step 2: Tissues and tissue interstitial fluid were separated by low speed centrifugation to obtain tissue interstitial fluid.

The cutting tissues were collected and further cultured by PBS solutions in an incubator at 37° C., 10% CO₂ condition for 60 minutes. Then the culture broths were centrifuged at 1000-2000 rpm/min for 2-5 minutes for removing cells to obtain a crude tissue interstitial fluid.

Step 3: The crude tissue interstitial fluid were centrifuged again to remove undissolved matrix by high speed centrifugation to obtain a pure tissue interstitial fluid.

To obtain pure tissue interstitial fluids respectively from liver cancer tissues and non-cancer liver tissues, the crude tissue interstitial fluids were centrifuged at 5000-15000 rpm/min for 15-30 minutes to remove the undissolved matrix and obtain a pure tissue interstitial fluid.

Step 4: Candidate biomarkers for hepatoma detection were selected.

The electropherograms of FIGS. 2A and 2B illustrate the unique 2-DE and 2-D DIGE patterns of the diseased (liver cancer) and normal (non-cancer liver) tissues. The representative images of two-dimensional gel electrophoresis (2-DE) (FIG. 2A) and two-dimensional differential fluorescence gel electrophoresis (2-D DIGE) (FIG. 2B). 2-DE was performed on immobilized pH 4-7 gradient strips, followed by the second-dimensional separation on 10-16% gradient polyacrylamide gels. For 2-DE, the separated proteins were stained with SYPRO Ruby. Images were captured, and relative volumes for each protein were normalized, matched across gels and determined with the aide of software analysis. For 2-D DIGE, equal amount of protein lysate from TIF (hepatoma interstitial fluid) and NIF (non-hepatoma interstitial fluid) were labeled with Cy3 and Cy5 dyes respectively, and vice versa, using the minimal labeling procedures. TIF and NIF were mixed together and then separated by 2-dimensional gel electrophoresis. Proteins with significant differentiation between TIF and NIF were selected for protein identification using mass spectrometry (matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry, MALDI-TOF/TOF MS). Results showed that the concentrations of ERBB3 (v-erb-b2 erythroblastic leukemia viral oncogene homolog 3) protein and IGFBP2 (Insulin-like growth factor binding protein 2) protein in the tissue interstitial fluid of the liver cancer tissues were higher than them appeared in the tissue interstitial fluid of non-cancer liver tissues.

Furthermore, the tissue interstitial fluids obtained from liver cancer tissues and non-cancer liver tissues were also analyzed by Antibody Array (Human Cytokine Antibody Array G Series 2000, RayBiotech Inc.) method, comprising:

A. 100 mg tissue interstitial fluids were dropped on each reaction well of the array chip for reaction at room temperature for 2 hours.

B. The reaction wells were washed by washing solution for 5 times, and the blocking buffer was mixed well with antibodies which had linked with biotin.

C. The blocking buffer containing antibodies linked with biotin were added into each reaction wells at room temperature for 2 hours.

D. The blocking buffer containing antibodies linked with biotin were removed. Then the reaction wells were washed by washing solution for 5 times, and a diluted Cy3-conjugated streptavidin which was included in the kit were added for reacting in dark at room temperature for 2 hours.

E. The Cy3-conjugated streptavidin were removed and the reaction wells were washed again by washing solution for 5 times and dried in dark at room temperature.

F. With reference to FIG. 3, the results showed on the protein array were read by Confocal Scanner Chip Reader. The strength of fluorescence showed on the protein array was further analyzed by Gene Pix Pro 4.1 software. Results showed that both concentrations of ERBB3 protein and IGFBP2 protein in the tissue interstitial fluids of the cancer tissues were higher than the non-cancer tissues. ERBB3 protein and IGFBP2 protein were selected as candidate biomarkers for hepatoma detection.

Complete amino acid sequence of ERBB3 protein was shown as SEQ ID NO. 1, and nature amino acid sequence in human serum was shown as SEQ ID NO: 2. Sequence of SEQ ID NO: 2 is same as the sequence from the 20 to 643 amino acid sequence of SEQ ID NO: 1. Complete amino acid sequence of IGFBP2 was shown as SEQ ID NO: 3, and nature amino acid sequence in human serum was shown as SEQ ID NO: 4. Sequence of SEQ ID NO: 4 is same as the sequence from the 40 to 328 amino acid sequence of SEQ ID NO: 3.

Step 5: The candidate biomarkers were used for hepatoma detection

A. Detect the Concentrations of ERBB3 Protein and IGFBP2 Protein in Serum:

To measure the concentration of ERBB3 protein and IGFBP2 protein correctly, ELISA methods comprised human ErbB3 kit (DY348) and human IGFBP2 kit (DY674) (R&D Systems Europe, Ltd) were used. Human ErbB3 protein and human IGFBP2 proteins which were produced by genetic engineer technology were used as standard.

Antibody for detecting ERBB3 protein in ELISA assay:

1. Capture antibody: an antibody which could bind to SEQ ID NO: 2 (R&D Systems, MAB 3481).

2. Detection antibody: a biotinylated monoclone antibody which could bind to SEQ ID NO: 2 (R&D Systems, BAM348).

ELISA antibody for IGFBP2 proteins:

1. Capture antibody: an antibody which could bind to SEQ ID NO: 4 (R&D Systems, MAB6741).

2. Detection antibody: a biotinylated antibody, goat IgG, which could bind to SEQ ID NO: 4 (R&D Systems, BAF674).

Steps for operation:

(a) Both capture antibodies were diluted to the concentration of 4 mg/ml, and added 100 μl to each reaction well at room temperature for reacting overnight;

(b) The obtained serum were diluted (the average dilution rate 10-100×), and 100 μl diluted serum were added into each reaction well at room temperature for 2 hours;

(c) The diluted serum were removed and the reaction wells were washed by wash solution, then 2 mg/ml of 100 μl biotinylated detection antibodies were added into each reaction wells at room temperature for 2 hours;

(d) The reaction wells were washed again, and streptavidin-HRP which was included in the kit was added and reacted in dark at room temperature for 20 minutes;

(e) The reaction wells were washed again, the subtracts which was also included in the kit were added for reaction at room temperature for 20 minutes;

(f) The data were read by microplate reader at 450 nm and 540 nm and corrected by 540 nm absorption as background value. After correction, the true absorption values were obtained. Then, the concentration of ERBB3 proteins and IGFBP2 proteins were evaluated by comparing with the concentration of standard samples.

Serum samples were collected from 113 liver cancer patients and 111 non-liver cancer patients (including 47 cirrhosis patients, 64 chronic hepatitis B) underwent the concentration of ERBB3 and IGFBP2 in serum samples for liver cancer detection.

With reference to FIGS. 4 to 6, the concentrations of serum ERBB3 protein and serum IGFBP2 protein in 113 liver cancer patients and 111 non-liver cancer patients were analyzed by student t-test to understand the difference. Results showed that false-positive values were less than 1/100 and p<0.01 were preliminarily selected for further analysis. The concentrations of serum ERBB3 proteins and serum IGFBP2 proteins, which showed a significant difference, were following analyzed by ROC curve analysis.

B. ROC Curve Analysis

To further understand whether ERBB3 protein and IGFBP2 protein were suitable for being markers for liver cancer detection, we provided another two group samples for each candidate markers for further check.

For IGFBP2 protein check experiment, there were 57 liver cancer patients and 35 non-liver cancer patients in Group I (taken as discovery group), and there were 56 liver cancer patients and 36 non-liver cancer patients in Group II (taken as validation group).

For ERBB3 protein check experiment, there were 56 liver cancer patients and 32 non-liver cancer but with hepatitis B patients in Group I (taken as discovery group), and there were 57 liver cancer patients and 32 non-liver cancer but with hepatitis B patients in Group II (taken as validation group). Results were shown in table 1 and table 2, respectively.

TABLE 1 Concentrations of IGFBP2 protein in serum Group I (Discovery Group) Group II (validation Group) Liver Non-liver Liver Non-liver cancer cancer cancer cancer patient patient patient patient (ng/ml) (ng/ml) (ng/ml) (ng/ml) 1 43.48484 37.16512915 1 101.4429 29.72011915 2 42.84814 27.8824984 2 67.78099 34.66665435 3 94.947 32.18498435 3 74.59434 29.72011915 4 51.20713 26.6626694 4 72.53931 26.6626694 5 94.23048 20.6265424 5 49.26238 20.02870635 6 102.898 36.538935 6 347.0552 25.4470416 7 113.2013 26.6626694 7 898.2424 26.6626694 8 66.43093 30.95045115 8 69.13526 38.42066835 9 47.32708 23.0283896 9 73.22327 36.538935 10 63.07414 31.5671926 10 61.07267 23.0283896 11 78.73277 12.352415 11 72.53931 19.4319206 12 175.1997 27.8824984 12 59.08066 32.8038264 13 99.99205 23.0283896 13 1059.827 40.3118544 14 32.80383 27.8824984 14 158.0795 23.0283896 15 29.72012 21.8253654 15 202.1783 29.72011915 16 73.22327 29.1065286 16 31.56719 31.5671926 17 118.4302 33.42371875 17 54.46938 42.21249315 18 150.8841 32.18498435 18 70.49373 21.22542875 19 61.73878 32.8038264 19 47.32708 25.4470416 20 58.41875 19.4319206 20 72.53931 35.91379115 21 176.8544 15.28382875 21 103.6272 21.22542875 22 84.30948 37.7923736 22 57.0981 21.22542875 23 46.04213 30.95045115 23 108.024 24.84080315 24 143.7737 14.6954454 24 49.90958 21.8253654 25 35.91379 36.538935 25 69.81397 21.22542875 26 37.16513 19.4319206 26 57.7579 28.49398835 27 116.183 21.22542875 27 35.91379 13.5218296 28 82.909 21.22542875 28 150.0898 26.05433035 29 792.7261 21.22542875 29 131.3431 22.42635235 30 76.65883 19.4319206 30 112.4586 30.95045115 31 115.436 67.7809926 31 142.9889 15.8732624 32 89.24425 14.10811235 32 283.8218 13.5218296 33 100.717 12.93659715 33 75.96962 30.33476 34 286.6897 17.64786515 34 38.42067 39.0500134 35 84.30948 15.8732624 35 162.1137 42.84814 36 43.48484 36 785.7038 15.28382875 37 77.34909 37 196.1848 38 75.96962 38 63.07414 39 80.12064 39 55.78164 40 47.32708 40 181.0094 41 55.12499 41 95.66457 42 42.21249 42 35.2897 43 37.79237 43 59.08066 44 31.56719 44 36.53894 45 35.2897 45 35.2897 46 32.18498 46 36.53894 47 147.7134 47 30.33476 48 49.26238 48 63.07414 49 38.42067 49 52.50888 50 40.31185 50 46.04213 51 65.75747 51 162.1137 52 70.49373 52 283.8218 53 42.21249 53 71.8564 54 55.78164 54 31.56719 55 61.73878 55 32.18498 56 42.84814 56 42.21249 57 42.21249

TABLE 2 Concentrations of ERBB3 protein in serum Group I (Discovery Group) Group II (Validation Group) Liver Non-liver Liver Non-liver cancer cancer cancer cancer patient patient patient patient (ng/ml) (ng/ml) (ng/ml) (ng/ml) 1 819.626 136.066 1 768.546 1106.586 2 666.386 187.146 2 1023.946 289.306 3 1177.186 238.226 3 2505.266 289.306 4 2403.106 187.146 4 1381.506 340.386 5 1279.346 289.306 5 1892.306 187.146 6 921.786 136.066 6 1483.666 646.866 7 1483.666 289.306 7 1126.106 391.466 8 1534.746 62.346 8 921.786 62.346 9 870.706 442.546 9 2096.626 289.306 10 819.626 544.706 10 2249.866 136.066 11 1279.346 902.266 11 768.546 187.146 12 1075.026 187.146 12 870.706 62.346 13 1687.986 595.786 13 870.706 136.066 14 7306.786 136.066 14 1177.186 62.346 15 1687.986 271.84 15 972.866 238.226 16 819.626 271.84 16 1790.146 339.2 17 1228.266 372.88 17 1228.266 137.12 18 666.386 406.56 18 1841.226 305.52 19 1177.186 406.56 19 1177.186 69.76 20 2096.626 137.12 20 1075.026 69.76 21 972.866 810.72 21 1432.586 574.96 22 541.586 204.48 22 1279.346 103.44 23 1330.426 642.32 23 921.786 204.48 24 870.706 305.52 24 1841.226 36.08 25 1687.986 372.88 25 1126.106 473.92 26 768.546 271.84 26 1126.106 204.48 27 870.706 541.28 27 1177.186 238.16 28 972.866 137.12 28 1177.186 473.92 29 1432.586 204.48 29 1330.426 170.8 30 666.386 58.16 30 666.386 291.68 31 870.706 204.11 31 768.546 116.54 32 921.786 466.82 32 921.786 320.87 33 1381.506 33 666.386 34 1228.266 34 768.546 35 768.546 35 819.626 36 8685.946 36 921.786 37 1330.426 37 1023.946 38 717.466 38 870.706 39 1075.026 39 1177.186 40 1177.186 40 5825.466 41 1636.906 41 1177.186 42 819.626 42 1330.426 43 1177.186 43 768.546 44 717.466 44 1177.186 45 1841.226 45 972.866 46 972.866 46 972.866 47 972.866 47 768.546 48 1023.946 48 1075.026 49 819.626 49 819.626 50 1652.72 50 305.52 51 608.64 51 4650.24 52 507.6 52 1955.84 53 2730.48 53 1046.48 54 878.08 54 574.96 55 676 55 2797.84 56 1248.56 56 204.48 57 271.84

The concentrations data shown in table 1 and table 2 were further described as follow:

(1) Results showed that ERBB3 proteins was a proper biomarker for liver cancer (hepatoma) detection

(i) With reference to FIG. 4, the ERBB3 protein concentration in serum in 113 liver cancer patients were higher than 47 cirrhosis without liver cancer patients (p<0.0001, student's t-test), and also higher than 64 chronic hepatitis B patients (p<0.0001, student's t-test).

(ii) With reference to FIG. 5A, the AUC values of Group I which had 56 liver cancer patients and 32 non-liver cancer but with hepatitis B patients was 97.7%.

(iii) With reference to FIG. 5B, the AUC values of Group II which had 57 liver cancer patients and 32 non-liver cancer but with hepatitis B patients was 96.1%.

(iv) With reference to FIG. 5C, analyzing by the cut-off value of Youden index, the sensitivity value for detecting liver cancer was 89.3% after combining Group I and Group II patient samples, and the specificity value was 99.7%. Similarly, by analyzing AFP in serum, the AUC values of the liver cancer patients and non-liver cancer patients were 91.5% after combining the two groups, but the AUC values of ERBB3 proteins only were 96.8%.

The above results showed that analyzed by the concentration of ERBB3 protein in serum is more sensitive than analyzed by AFP in serum. Therefore, it is powerful to use ERBB3 protein as a biomarker for detecting liver cancer.

(2) Results showed that IGFBP2 proteins was a proper biomarker for liver cancer (hepatoma) detection

(i) With reference to FIG. 6, the concentration of IGFBP2 protein in serum in 113 liver cancer patients were higher than 47 cirrhosis without liver cancer patients (p<0.001, student's t-test), and also higher than 64 chronic hepatitis B patients (p<0.001, student's t-test).

(ii) With reference to FIG. 7A, the AUC value of the serum in Group I which had 57 liver cancer patients and 35 hepatitis B without liver cancer patients were 96.4%.

(iii) With reference to FIG. 7B, the AUC value of the serum in Group II which had 56 liver cancer patients and 36 hepatitis B without liver cancer patients were 96.24%.

(iv) With reference to FIG. 7C, the AUC value was 96.2% after combing Group I and Group II patient samples. However, by detecting AFP in serum, the AUC values of the liver cancer patients and non-liver cancer patients were 71.5% after combining the two Groups. Therefore, detecting by the concentration of IGFBP2 in serum to identify liver cancer patients and non-liver cancer with hepatitis B patients were more sensitive and specificities than detecting by AFP values.

The above results showed that analyzed by the concentration of IGFBP2 protein in serum is more sensitive than analyzed by AFP values in serum. Therefore, it is powerful to use IGFPB2 protein as a biomarker for detecting liver cancer.

Combination detection of AFP, ERBB3 protein and IGFBP2 protein in serum to increase the sensitivity and specificity of liver cancer detection

(i) The AUC values of AFP, ERBB3 and IGFBP2 were 84.3%, 96.8% and 96.1%, respectively.

(ii) With reference to FIGS. 8A and 8B, the AUC values of AFP+ERBB3 and AFP+IGFBP2 were 96.9% and 94.5%, respectively. With reference to FIG. 8C, the AUC value of ERBB3+IGFBP2 was 98.5%. Furthermore, with reference to FIG. 8D, the AUC value of AFP+ERBB3+IGFBP2 was 99.1%. Therefore, to increase the sensitivity and specificity to almost 100%, it is very useful to combine AFP value, ERBB3 value and IGFBP2 value for diagnosis of hepatoma.

The present invention is not to be limited in scope by the specific embodiments described herein. Indeed, various modifications of the invention in addition to those described herein will become apparent to those skilled in the art from the foregoing description. Such modifications are intended to fall within the scope of the appended claims.

All patents, applications, publications, test methods, literature, and other materials cited herein are hereby incorporated by reference. 

1. A method for detection of liver cancer, comprising steps of: a) providing a liquid sample obtained from an individual, b) contacting said sample with an antibody specific for at least one of IGFBP2 protein (SEQ ID NO: 4) under conditions appropriate for formation of a complex between said antibody and at least one of said proteins, and c) correlating an amount of the complex formed in step d) to the detection of liver cancer. 2-3. (canceled)
 4. The method according to claim 1 wherein the liquid sample is whole blood. 5-9. (canceled) 